Senior Software Engineer

Team: IT

Location: Canada

Commitment: Full-time

Workplace Type: remote

Accountabilities:

Design and develop machine learning infrastructure: Build and maintain scalable systems that support advanced machine learning algorithms, including supervised learning, unsupervised learning, and deep learning, to identify suspicious patterns and fraudulent behavior.
Develop distributed real-time systems: Design, implement, and optimize distributed architectures that enable real-time data processing and fraud detection across high-volume datasets.
Build large-scale data pipelines: Leverage big data technologies such as Apache Spark, Hadoop, HBase, and Cassandra to develop efficient machine learning pipelines and process data from large consumer-facing platforms.
Implement streaming solutions: Develop and maintain real-time data processing systems using technologies such as Apache Kafka and Apache Flink to support rapid detection and analysis of emerging fraud patterns.
Improve detection capabilities: Collaborate with machine learning specialists to enhance detection algorithms, optimize data processing workflows, and support the continuous improvement of fraud detection performance.
Build engineering tools and validation frameworks: Develop internal systems, tools, and testing strategies that support new features, validate system behavior, and maintain software quality.
Optimize system performance: Identify bottlenecks and improve the scalability, reliability, efficiency, and responsiveness of distributed services and data infrastructure.
Contribute to architectural decisions: Participate in technical design discussions and help develop robust, maintainable architectures for complex data-intensive applications.
Support continuous innovation: Explore and implement engineering approaches that improve real-time analytics, automated model training, and the ability to respond to evolving fraud techniques.
Collaborate across technical teams: Work with software engineers, machine learning experts, and infrastructure specialists to deliver reliable solutions and advance the platform's technical capabilities.
Requirements:
Professional experience: At least five years of professional software development experience, with a strong background in building and maintaining production-grade systems.
Programming expertise: At least five years of experience developing software with Java, Python, and Shell scripting, including the ability to write efficient, reliable, and maintainable code.
Database knowledge: Strong understanding of relational databases, SQL, and database design. Familiarity with object-relational mapping technologies such as JPA2 and Hibernate is an advantage.
Distributed systems and big data: Experience with one or more technologies such as Apache Cassandra, HBase, Spark, Hadoop, Flink, or Kafka is highly desirable.
Machine learning infrastructure: Interest or experience in supporting machine learning systems, large-scale data processing, streaming architectures, or automated data pipelines.
Software engineering best practices: Ability to design scalable systems, troubleshoot complex technical issues, optimize performance, and maintain high standards of code quality.
Testing and validation: Familiarity with test-driven development, automated testing, and validation techniques is an asset.
Problem-solving abilities: Strong analytical and critical-thinking skills, with the ability to address complex engineering challenges in distributed and data-intensive environments.
Collaboration and communication: Ability to work effectively with multidisciplinary engineering teams, communicate technical concepts clearly, and contribute constructively to design discussions.
Adaptability and continuous learning: Demonstrate curiosity and enthusiasm for emerging technologies, machine learning infrastructure, and innovative approaches to real-time fraud detection.
Location and remote work: Be based in Canada and comfortable working remotely. Candidates located in Calgary are preferred, although fully remote arrangements are available.
Benefits:
Competitive compensation: Annual salary ranging from CAD $120,000 to CAD $150,000, depending on experience and qualifications.
Extended health coverage: Access to health insurance benefits, including extended healthcare services.
Vision care: Coverage for eligible vision-related healthcare expenses.
Dental insurance: Access to dental care benefits.
Life insurance: Financial protection through life insurance coverage.
Accidental insurance: Additional insurance coverage for eligible accidental events.
Retirement savings plan: Access to a retirement savings program to support long-term financial planning.
Paid vacation: Paid time off to support rest, personal commitments, and work-life balance.
Remote work flexibility: Opportunity to work remotely from Canada, with Calgary identified as a preferred location.
Advanced technical challenges: Work with large-scale machine learning systems, distributed architectures, and modern streaming technologies.
Collaborative engineering culture: Join a results-oriented team that values innovation, technical excellence, and knowledge sharing.
Meaningful impact: Contribute to technologies that help organizations detect fraud, strengthen security, and protect digital transactions.